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languages such as Python or R. Experience with machine learning, systems biology, or network modeling approaches. Previous expertise in human cardiometabolic or complex diseases, with domain expertise in but
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budget of DKK 3 billion. Learn more about The Faculty of Science at www.science.ku.dk You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/ . When you will be
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centres on mathematical models of the physical and virtual world, as a basis for the analysis, design, and implementation of complex systems. We focus on ensuring that our research results contribute
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to transform the entire structure and functioning of Arctic coastal marine ecosystems. CIFAR is a research center that aims to unravel how the complex interplay between ice melt, runoff and ice formation across
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interdisciplinary environment of the Danish Polymer Centre. Elastomers’ complex mechanical behavior under varying conditions makes accurate prediction challenging. In this project, you will design and implement
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to support decision-making by integrating physical models and sensor data. These methods are validated through industrial case studies, with a particular emphasis on critical infrastructures where complexity
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that pose serious ecological and health risks. Their low concentration and complex behavior make experimental analyses challenging. Developing reliable predictive models is essential to reduce the reliance
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languages such as Python or R. Experience with machine learning, systems biology, or network modeling approaches. Previous expertise in human cardiometabolic or complex diseases, with domain expertise in but
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entails that teaching will be one third of the workload. To fulfill the research requirements of the position, the applicant chosen is expected to be physically present on a regular basis and actively
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The Department of Molecular Biology and Genetics at Aarhus University is a vibrant and exciting interdisciplinary research environment. The department is located in a newly renovated laboratory complex with well